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PROCESSING FUNDUS CAMERA IMAGES USING MACHINE LEARNING MODELS TRAINED USING OTHER MODALITIES

机译:使用使用其他方式培训的机器学习模型加工眼底相机图像

摘要

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a fundus image processing machine learning models that is configured to process one or more fundus images captured by a fundus camera to generate a predicted label. One of the methods includes generating training data, comprising: receiving sets of one or more training fundus images captured by a fundus camera; receiving, for each of the sets, a ground truth label assigned to a different image of the eye of the patient corresponding to the set that has been captured using a different imaging modality; and generating, for each set of training fundus images, a training example that includes the set of training fundus images in association with the ground truth label assigned to the different image of the patient's eye; and training the machine learning model on the training examples in the training data.
机译:方法,系统和装置,包括在计算机存储介质上编码的计算机程序,用于训练用于处理由眼底照相机捕获的一个或多个基底图像以生成预测标签的眼底图像处理机器学习模型。其中一个方法包括生成培训数据,包括:接收由眼底相机捕获的一个或多个训练基底图像的组;接收到每个集合,将分配给与已经使用不同的成像模型捕获的集合对应的患者眼睛的眼睛的不同图像的地面真理标签;对于每组培训基底图像,以及包括与分配给患者眼睛不同图像的地面真理标签的培训示例,包括该集的培训示例。并在训练数据中培训训练示例的机器学习模型。

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